pandas GroupBy.agg()引发TypeError:aggregate()缺少1个必需的位置参数:'arg' [英] Pandas GroupBy.agg() throws TypeError: aggregate() missing 1 required positional argument: 'arg'

问题描述

我正在尝试创建同一字段的多个聚合.我正在使用python3.7在熊猫中工作.根据文档，语法似乎非常简单:

I’m trying to create multiple aggregations of the same field. I’m working in pandas, in python3.7. The syntax seems pretty straightforward based on the documentation:

https://pandas-docs. github.io/pandas-docs-travis/user_guide/groupby.html#named-aggregation

我看不到为什么出现以下错误.有人可以指出这个问题并告诉我如何解决吗?

I do not see why I’m getting the error below. Could someone please point out the issue and tell me how to fix it?

代码:

qt_dy.groupby('date').agg(std_qty=('qty','std'),mean_qty=('qty','mean'),)

错误:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-62-6bb3aabf313f> in <module>
      5 
      6 qt_dy.groupby('date')\
----> 7 .agg(std_qty=('qty','std'),mean_qty=('qty','mean'))

TypeError: aggregate() missing 1 required positional argument: 'arg'

推荐答案

好像您正在尝试将agg与

Looks like you're trying to use agg with Named aggregations—this is a supported feature from v0.25 and above ONLY.

对于旧版本，您将需要使用元组格式列表:

For older versions, you will need to use the list of tuples format:

qt_dy.groupby('date')['qty'].agg([('std_qty','std'), ('mean_qty','mean')])

或者，为了汇总多列字典，

Or, to aggregate multiple columns, a dictionary:

qt_dy.groupby('date').agg({'qty': [('std_qty','std'), ('mean_qty','mean')]})

有关更多信息，请在此处查看我的答案.

For more information, take a look at my answer here.

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